xdiss {mvpart}R Documentation

Extendend Dissimilarity Measures

Description

The function computes extended dissimilarity indices which are for long gradients have better good rank-order relation with gradient separation and are thus efficient in community ordination with multidimensional scaling.

Usage

xdiss(data, dcrit = 1, dauto = TRUE, dinf = 0.5, method = "man", 
    use.min = TRUE, eps = 1e-04, replace.neg = TRUE, big = 10000,
    sumry = TRUE, full = FALSE, sq = FALSE) 

Arguments

data Data matrix
dcrit Dissimilarities < dcrit are considered to have no species in common and are recalculated.
dauto Automatically select tuning parameters – recommended.
method Dissimilarity index
use.min Minimum dissimilarity of pairs of distances used – recommended.
dinf, eps, replace.neg, big Internal parameters – leave as is usually.
sumry Print summary of extended dissimilarities?
full Return the square dissimilarity matrix.
sq Square the dissimilarities – useful for distance-based partitionong.

Details

The function knows the same dissimilarity indices as gdist.

Value

Returns an object of class distance with attributes "Size" and "ok". "ok" is TRUE if rows are not disconnected (De'ath 1999).

Author(s)

Glenn De'ath

References

De'ath, G. (1999) Extended dissimilarity: a method of robust estimation of ecological distances from high beta diversity data. Plant Ecology 144(2):191-199.

Faith, D.P, Minchin, P.R. and Belbin, L. (1987) Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57-68.

Examples

data(spider)
spider.dist <- xdiss(spider)

[Package mvpart version 1.2-6 Index]